Note: The job is a remote job and is open to candidates in USA. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. They are seeking a Forward Deployed AI Engineer to act as a trusted advisor to customers, driving business value and offering advice on GenAI and ML best practices.

Responsibilities

• Work closely with some of the most sophisticated ML / GenAI teams in the world
• You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders
• Advise on GenAI and ML best practices
• Give ML and LLM product demos to technical and business stakeholders
• Run strategic business reviews for customers in partnership with our sales team
• Interface with our pre-sales engineering team to gather client goals and KPI’s
• Partner with our product and engineering teams to help drive the product roadmap
• Spearhead new opportunities within existing accounts to help drive expansions

Skills

• Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production
• Comfortable working in public Cloud environments (AWS, Azure, GCP)
• Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
• Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
• Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
• Understanding of GenAI concepts and application evaluation + development lifecycle
• Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
• Strong Communication Skills - Ability to simplify complex, technical concepts
• A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV
• Previous engineering experience in: Data Science, MLOps, ML Frameworks, LLM / Agentic frameworks
• Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
• Prior experience working with applications deployed with Kubernetes
• Prior experience demoing technical products to both business and technical audiences

Benefits

• A competitive equity package
• A comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support
• WFH monthly stipend to pay for co-working spaces

Company Overview

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